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What you made yesterday, after ads, shipping and fees

Connect the warehouse where your store, marketplace, retail and ad data meet, then ask in plain English: profit by channel, MER, stock cover, repeat buyers and returns.

For multi-channel consumer brands selling through their own store, marketplaces and retail, and their founders, finance and growth teams.

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All 9 questions

ChatCommerce agent

Profit yesterday after ads, shipping and fees

AI Analyst

You made $10,770 yesterday after ads, shipping and fees: 22.2% of $48,620 in net sales. Ads were the biggest cost after product, at $11,460.

Net sales48,620

Product cost−18,240

Ads−11,460

Shipping−4,980

Fees−3,170

Profit10,770

Readordersorder_linesad_spend_dailyshipmentsSQL

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Sample data

Ask this on your own data

Every question, by who asks it

Taken from what teams in this industry ask Supaboard. Each one opens a free account with the question waiting.

01 · Profit and spend

02 · Customers

03 · Stock and returns

Keep it running

What teams keep on a schedule once they've asked the question once.

Report · Monday 08:00

The Monday profit pack

Last week's net sales, ads, shipping, fees and profit by channel, with MER against the week before, summarised and in the founders' inbox.

  1. Timed Start
  2. Query Your Data
  3. Summarize Insights
  4. Send Email

Alert · Every 5 minutes

Stock-cover watch

A SQL check finds any SKU under 30 days of cover with nothing on order, and emails the buyer while there's still time to reorder.

  1. Alerts
  2. Send Email

Datasite · Month end

The channel datasite

Units, revenue and margin for your own store, marketplaces and retail, on a private datasite the founders and investors sign in to with Google or Microsoft.

The numbers it keeps watch on

Standard definitions, and where each one lives in Supaboard once you've asked for it.

MeasureDefinitionSourceIn Supaboard
Profit after adsNet sales − product cost − shipping − payment and marketplace fees − ad spendCommon practiceMonday profit pack
MERNet sales across every channel ÷ total ad spend, for the same periodCommon practiceMonday profit pack
Channel marginNet sales − product cost − that channel's fees, for own store, marketplaces and retailCommon practiceChannel datasite
Days of stock coverUnits on hand ÷ average daily units sold over the last 14 days, across every channelCommon practiceAlert at 30 days
Repeat purchase rateFirst-time buyers in a period who order again ÷ first-time buyers in that periodCommon practiceMonthly question
90-day LTVNet sales per customer in the 90 days from their first order, by first productCommon practiceGrowth dashboard
Return rateUnits returned ÷ units sold, by product and sizeCommon practiceWeekly report
Code new-customer shareOrders with a discount code from first-time buyers ÷ all orders with that codeCommon practiceAsk it after each promotion

Where your data lives

Or attach an export to a conversation, as CSV or Excel:

  • XLSRetail sell-through reportsUpload
  • XLSStore and ad-platform exportsUpload

The tables these questions read:

  • Orders and order lines by channel, with discounts and refunds
  • Products and SKUs, with unit cost
  • Inventory by location, and open purchase orders
  • Ad spend by platform, campaign and day
  • Returns, with reason and size
  • Retail sell-through by account and week

Teach it your definitions once

Rules are read with every question, so a term means the same thing in Chat, in Slack and in the Monday report.

  • Rule“Profit means net sales minus product cost, shipping, payment and marketplace fees, and ad spend.”
  • Rule“The current sell rate is average daily units over the last 14 days, across every channel.”
  • Rule“A first-time buyer is a customer with no earlier order in the online store.”
How rules work

Already running on it

A multi-channel consumer brand runs Supaboard on its Redshift warehouse, where its online store, marketplace, retail and media-spend data meet: orders, inventory, shipping and campaigns.

A Supaboard customer, described without its name

Security

Read-only by construction

Database and warehouse queries are read-only. We give you the SQL for a read-only user too.

Credentials stay in the workspace

Scoped to the one workspace that connected them, never logged and never sent back to a browser.

SOC 2 Type II

An organisation-wide audit of the platform, covering every plan.

Frequently asked questions

Which store and ad platforms does it work with?

Any whose data reaches your warehouse. Redshift, BigQuery and Snowflake connect live, so store orders, marketplace sales and ad spend that land there are queried in place, read-only. There's no direct store or ad-platform connector: for a one-off question, export from the platform as CSV or Excel and attach it to a conversation.

How soon can we ask about our store data?

As soon as your warehouse is connected and its tables are indexed. It's queried in place, so answers are as fresh as the warehouse.

Can we try it before connecting anything?

Yes. Onboarding offers a sample online-store database, so you can ask about its orders, products and returns first.

How does it learn what we count as profit?

Write it once as a rule, such as "profit is net sales minus product cost, shipping, fees and ad spend". The agent reads its rules with every question, so profit means the same thing in Chat, in Slack and in the Monday report.

Can we get the numbers every Monday?

Yes. An automation runs your questions at 08:00 on Monday in your timezone, summarises what changed and emails it. Dashboard reports can also go out as PDF, PowerPoint or Excel.

Ask your first question on your own data

Connect a source, ask in plain English, and keep what you find.

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